Développement d’outils d’évaluation du milieu récepteur pour l’industrie minière
Bibliographic record
Abstract
From 2001 to 2004, we conducted a research project to develop tools for the ecological assessment of aquatic environments receiving mining effluents. These tools were designed to contribute to better define environmental discharge objectives for these types of effluents. Our project focused on two rivers in the Abitibi-James Bay mining region in northwestern Quebec. The most convincing results of our research include the development of a technique for the direct measurement of the free metal ion in solution (Cd, Ni, Zn); the validation of three organisms as biomonitors of trace metal contamination in lotic environments: the burrowing larvae of the Ephemera Hexagenia limbata, the amphipod crustacean Hyalella azteca, the bivalve Pyganodon grandis; and the identification of a laboratory toxicity test using the microalga Pseudokirchneriella subcapitata as a metal-sensitive assay to test waters from the receiving environment. De 2001 a 2004, nous avons mené un projet de recherche visant a développer et/ou à valider des outils de diagnostic des effets écotoxicologiques des effluents miniers dans le milieu aquatique afin de mieux définir des objectifs environnementaux de rejets pour l’industrie minière. Ce projet a été réalisé sur deux rivières de la région minière de l’Abitibi-Baie-James dans le nord-ouest du Québec. Parmi les outils diagnostiques les plus importants qui ont été développés et/ou validés, notons une technique de mesure directe de l’ion métallique libre en solution (Cd, Ni, Zn) ; l’utilisation de trois organismes comme biomoniteurs de contamination métallique en milieu lotique : la larve fouisseuse de l’éphémère Hexagenia limbata, le crustacé amphipode Hyalella azteca, le bivalve Pyganodon grandis ; et le test de toxicité en laboratoire, sur l’eau du milieu récepteur, avec la micro-algue Pseudokirchneriella subcapitata.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".